Anime Soccer

pika-labs/pika-plugins/skills/anime-soccer

作者 pika-labsf27b3ba28a7b無授權條款40 個星標收錄於 2026年10月9日更新於 2026年10月8日儲存庫2 個月前更新

Use when the user asks for anime soccer or a task matching the examples below. Put the USER into a ~45s Japanese-anime football short as the hero — from their photo + their favorite team + the opponent. Anime-fies the user's face into a consistent character sheet, designs a dramatic 3-act match (come on → equalizer → winner) with the user scoring, writes three 15s cel-shaded scene prompts (CAPS names + Japanese dialogue), generates them on Seedance off the sheets, and stitches them. A Japanese-anime football short built on the Pika MCP, but the star is YOU. Triggers: "/anime-soccer", "put me in an anime soccer video", "make me the anime football hero", "anime match with my photo". Requires the Pika MCP.

僅含說明Design & Creative
AI 產生的概覽

把使用者照片變成以本人為主角的三幕約45秒動漫足球短片,透過 Pika MCP 影片工具完成。

功能
引導代理依固定流程執行:先用使用者照片產生動漫角色設定圖,再設計一場以使用者所屬球隊對戰對手的三幕戲劇性比賽,撰寫三段15秒賽璐璐風格分鏡提示詞並搭配日文台詞,依設定圖逐段生成影片,最後拼接成片。產出約45秒、16:9、1080p 的動漫足球影片,以及三段個別的分鏡片段。文件也列出失敗情況與處理方式,例如重抽臉部漂移的鏡頭,或對觸發內容過濾的提示詞做去品牌化處理。
適用情境
適用於使用者希望把自己放進動漫足球短片的情境,例如透過 /anime-soccer 觸發,或提出「讓我成為動漫足球主角」的需求。適合能提供照片、球隊與對手資訊的要求。
執行需求
需要 Pika MCP 及其指定的影像編輯、參考影片與拼接工具,包括 nano-banana-pro 與 seedance 供應方,還需要使用者照片(本機路徑或連結)以及球隊與對手的球衣配色。需要連線至這些服務的網路;此技能未附帶指令碼。

anime-soccer

Turn the user into the hero of a 3-scene (~45s) Japanese-anime football short, but the star is the person running it. Each scene is a 15s cel-shaded anime beat with the user (named, in CAPS) and Japanese dialogue, generated on Seedance off an anime character sheet made from the user's photo, then stitched.

The proven pipeline (do not deviate from the order): user photo → anime CHARACTER SHEET (nano-banana-pro) → DESIGN the dramatic match + WRITE 3×15s scene prompts (you, acting as Claude) → SEEDANCE each scene off the sheet → STITCH.

The magic is in three things, in this order: (1) a character sheet so the user's anime likeness is consistent across every scene, (2) a specific, dramatic match designed for them (their team vs the opponent, real kit colors, a concrete goal mechanic each scene — not a generic "he scores"), (3) the scene-prompt formula (cel-shaded style tag + named hero in CAPS + camera/anime techniques + Japanese VO).


Stage 0 — Intake

Collect, in one pass (the only things that change per user):

  • The user's photo (required) — a clear face photo; this becomes the anime hero. Local path or URL. Likeness comes from this. Upload local files via upload_asset → use the public_url. (If on Claude Desktop where pasted images don't reach MCP, ask once for a URL or a .zip.)
  • On-screen hero name (optional) — what to call them in CAPS in the prompts + Japanese VO (e.g. "KAITO"). Default to their first name, or "THE STRIKER" if they'd rather not use a name.
  • Their team (required) — the hero's side. Capture the kit colors / stripe pattern (e.g. "sky-blue and white vertical stripes"), NOT the crest or sponsor (describe colors, not trademarks — see de-branding in failure modes).
  • The opponent (required) — who they're playing against. Capture the opponent's kit colors too. Opponent players (keeper, a defender) are generic — described by kit color, not named.

Confirm in one line ("Putting YOU in an anime match — [TEAM] vs [OPPONENT], you score the winner…"), then run the pipeline. No further yes/no gates.


Stage 1 — Anime character sheet (generate_image_edit, nano-banana-pro)

Generate ONE anime character sheet of the user from their photo. The sheet (multiple angles + full body + close-ups) is what keeps the face consistent across all three scenes.

Call generate_image_edit with:

  • provider: nano-banana-pro (REQUIRED default). It does reference-identity → anime stylization cleanly for any real face. Don't use gpt-image-2 here — OpenAI's safety system rejects anime-editing a real photo of an identifiable person (content_policy / image_generation_user_error).
  • images: [<the user's photo url>]
  • aspect_ratio: 16:9 · quality: high · output_format: png
  • prompt (verbatim template — fill {NAME}; put them in their team kit):
    Create a character sheet of this football player named {NAME} in a {TEAM kit colors} kit, with close-ups and full body shots from different angles in Japanese anime style.

Save the returned URL as state.sheets[HERO]. Inspect: the sheet must be clearly that person, anime-styled, with usable full-body + face angles. Re-roll if it drifts. (If the user also wants a named teammate/rival on screen with a real face, make a sheet per character the same way; otherwise opponents stay generic.)


Stage 2 — Design the match + write the 3 scene prompts (you = "Claude")

This is the step the creator did in Claude. You do it directly. There's no real game to research — you design a dramatic, specific match for the user, then WRITE it in the formula. Specificity is what sells it: pick a real goal mechanic for each scene, not "he scores."

  1. Design the match: the user's team ([TEAM]) vs [OPPONENT] in a huge night stadium. Decide the arc — the hero comes on with the team behind, equalizes, then scores a dramatic late winner. For each goal choose a concrete mechanic (a volley, a header off a cross, a turn-and-finish, a solo run, a free-kick) and a scoreline + minute. Use the two teams' kit colors throughout; opponent keeper/defenders by color only.

  2. Write exactly 3 scenes, 15s each, following the proven 3-act arc:

    • Scene 1 — "THE CALL": the hero comes on / kickoff for [TEAM], tension building, crowd roaring, a teammate or the bench urging them on.
    • Scene 2 — "THE EQUALIZER": the hero scores the equalizer vs [OPPONENT] with the chosen mechanic (real assist build-up, the strike, the keeper beaten) — e.g. 1-1.
    • Scene 3 — "THE WINNER": stoppage time, the hero scores the decisive goal, ending on the win + an on-screen final-score card.
  3. Scene-prompt formula (match this structure exactly — it's what makes it work):

    • Open with the style tag: Japanese anime action style, cel-shaded, high contrast, [color grade e.g. cold desaturated → blazing gold], [intensity], [setting: packed night stadium, the minute + scoreline].
    • Beat-by-beat action naming the hero in CAPS with their kit colors, the exact goal mechanic, and anime camera/FX language: extreme close-up on the eyes, low heroic angle pushing up, slow dolly-in, anime smear frames, bullet-time on the strike, impact frame flashes pure white then SNAPS to full speed, net ripples, golden particle burst, motion-blur trail, frozen goalkeeper mid-dive.
    • Mood line: e.g. brooding/determined → electric/triumphant → euphoric/explosive.
    • End with Japanese VO/subtitle lines, one per speaker, prefixed by the character's name, plus a commentator — short dialogue + the hero's inner monologue. Format:
      VO/subtitle (JP): {NAME}「…」 / {NAME} (inner)「…」 / commentator「…」
    • Scene 3 also gets a final on-screen card: Final on-screen card: {TEAM} {SCORE}.

    (Proven structural reference — the dramatic anime-match edit this format is modeled on; mirror its SHAPE exactly, swapping in YOUR hero name + YOUR team + the opponent: Scene 1 cold-graded close-up → strides on under floodlights, a teammate shouts, hero inner-monologue. Scene 2 a cross comes in → the HERO volleys it in, bullet-time + white impact flash, 1-1, keeper frozen. Scene 3 stoppage time, the HERO turn-and-spin finish past the defender, knee-slide, gold confetti, "[TEAM] 2-1" card. Each opens with the cel-shaded style tag and closes on JP dialogue + monologue + commentator. Reuse this shape; swap in your hero + teams + the goal mechanics you designed.)


Stage 3 — Generate each scene (generate_reference_video, seedance)

One call per scene. Use the character sheet as reference and map the hero name to the image via the Seedance @Image1 token.

Call generate_reference_video with:

  • provider: seedance · seedance_backend: ark
  • reference_images: the hero sheet (plus any extra character sheets used in THAT scene) — e.g. [sheets[HERO]]
  • aspect_ratio: 16:9 · resolution: 1080p · duration: 15 · sound: true (the JP dialogue + dramatic SFX are the point here — this format KEEPS generated voice/audio)
  • prompt: a name→image mapping line, then the scene prompt. Example:
    {HERO} is @Image1. <full Scene 1 prompt from Stage 2>
    Reference the hero via its @ImageN token where it first appears so Seedance binds the likeness.

Fire all three in parallel (background: true) and poll. Re-roll a scene if: the goal mechanic is wrong, the face drifts off the sheet, or the title/score card text garbles. If a scene trips OutputAudioSensitiveContentDetected, re-roll with a new seed (or, as a last resort, sound: false for that scene only and add the dialogue as an overlay).


Stage 4 — Stitch

Concatenate Scene 1 → 2 → 3 in order into the final ~45s, 16:9 1080p cut (edit_concat, or ffmpeg concat of normalized clips). Keep each scene's generated audio. Optionally lay a subtle epic-anime music bed under it (post-only) if the user wants one. Deliver the stitched MP4 + the 3 scene clips.


Settings quick-reference

StepToolKey settings
Character sheetgenerate_image_editnano-banana-pro (gpt-image-2 rejects real-person photos), ref = user's photo, hero in team kit, 16:9
Design + promptsyou (acting as Claude)a specific dramatic match → 3×15s scenes in the formula above
Scene videogenerate_reference_videoseedance/ark, sheet as ref, name→@ImageN map, 16:9, 1080p, 15s, sound:true
Stitchedit_concat / ffmpegscenes in order, keep audio, ~45s

Optional: seedance-anime (style help for the prompt voice) and seedance-director can assist with shot phrasing — but the formula above already reproduces the target look.

Failure modes

SymptomFix
Face changes between scenesAlways pass the character sheet (not the raw photo) as the reference on every scene; re-roll drifters; map the hero to its @ImageN.
Goal looks generic / weakYou skipped the design step — pick a specific mechanic (volley / header / turn-and-finish), a scoreline, kit colors, and write the strike beat-by-beat.
Hero unnamed / no Japanese dialogueThe formula is mandatory: name the hero in CAPS, end every scene with the VO/subtitle (JP): … block.
Score / title card text garbledKeep card text short ("[TEAM] 2-1"); re-roll; or burn it as a clean overlay in post.
Audio sensitive-content trip (OutputAudioSensitiveContentDetected)Re-roll seed; last resort sound:false for that scene + overlay the JP lines.
Copyright/sensitive-content trip on the VIDEO (OutputVideoSensitiveContentDetected)A new seed alone won't clear it — it's the content. Walkout / ceremony / broadcast-style scenes trip it most. De-brand the prompt: no named tournament ("World Cup" → "a huge night stadium"), no real club crests/sponsor logos, no on-screen scoreboard / lower-thirds / broadcast graphics, no captain's armband. Describe kit COLORS only, keep it pure on-pitch action (open-play goal scenes pass first try).
Transient invalid_input / "Unknown provider: seedance-assets" / skill_crashed mid-jobPika-side backend hiccup, not your input. Re-fire the same call with a new seed. If it ran past ~4 min before failing, the content already cleared the safety pass.
content_policy / image_generation_user_error on the character sheetgpt-image-2 (OpenAI) blocks anime-editing a real person's photo. Use nano-banana-pro for the sheet (the default); don't retry gpt-image-2 with the same photo.

Notes

  • Pipeline: image-sheet → designed scene prompts → Seedance 15s scenes → stitch — built entirely on the Pika MCP, with the user as the hero (their photo + team + opponent).
  • Default output: 3 scenes × 15s = ~45s, 16:9, 1080p, anime cel-shaded, Japanese VO. Aspect/length configurable if the user asks (e.g. 9:16 for reels).

來源與署名

來源:pika-labs/pika-plugins位於skills/anime-soccer提交f27b3ba

授權條款: 無授權條款

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